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CHAPTER 4 ANALYSIS OF FERTILITY DETERMINANTS AT THE NATIONAL LEVEL This chapter uses multivariate regression analysis to explain how changes in average parity among married women in Brazil relate to their changing socioeconomic charac- teristi~s during the accelerated fertility decline of the early 1970s. In so doing, it attempts to provide a more systematic assessment of the hypotheses presented in the last two chapters, supported by tabular evidence, about socioeconomic differences in fertility decline in Brazil and the forces behind those dif ferences. The decision to focus on variability in the average parity of married women was based on several considera- tions. First, fertility was measured according to average par ity rather than the last birth reported because of the questionable reliability and comparability of the latter in studying changes over time among different socioeco- nomic groups. Second, analysis of the proximate deter- minants of the decline in the total fertility rate between 1970 and 1976 indicated fertility control by married women to be the major factor involved; this conclusion was also supported by evidence on the diffusion of contraception among new regions and income groups. Third, accelerated fertility decline coincided with a number of important socioeconomic changes that could have had an impact on the motivation to control fertility, including increases in female educational attainment and possible aggravation of inflationary pressures on the economic resources of low- and middle-income households. The last two points sug- gested a working hypothesis about the acceleration of fertility decline: that it was triggered by the conver- gence of two sets of forces--increased availability of effective means of contraception and the emergence of socioeconomic conditions conducive to smaller family norms . 115

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116 Because there is a lack of nationally representative data combining information on contraceptive use and socio- economic characteristics, the analysis in this chapter is 1 imited to the second set of forces. The pr inc~pal aues- tion addressed is the extent to which the effects on reproductive behavior of such modernizing forces as increased household income and f emale educational attain- ment (as measured by average parity) combined with other factors affecting household behavior, particularly those reflecting such major structural dimensions of the Brazil° Ian economy as inflation and income distribution. Differs ential patterns of change among rural and urban areas sug- gested a division of ache chapter into separate sections for these groups, though work on the latter was even more rests i<:ted by data limitations . URBAN WOMEN As noted earlier, the acceleration of fertility decline in Brazil coincided with a period during which lower- and middle-income urban households were raising their consump- tion expectations end beginning to realize them through increased purchases of housing and other consumer dur ables, including televisions and automobiles, with most purchases made on the installment plan O Unequal treatment of wages and credit obligations in Brazil's indexing sys- tem made it more difficult for families to keep up with payments, and even to purchase basic necessities during periods of high inflation. As was suggested earlier, this, combined with increased knowledge of and access to contraception, may have reduced family-size desires. This explanation does not compete with a modernization frame- work, but extends it to incorporate other structural changes. Along the research questions that need to be addressed are the Following: (1) What measures in the available data files can be used as appropriate indices of the mod- ern~zing forces and economic pressures discussed above? ( 2) Mow should the relationship between these measures and average par ity be specif led? Are the relationships line ear? Should interactions be taken into account? (3) Can the analysis be pushed beyond explanation of differentials in average parity in 1970 and 1976 to an assessment of the sources of change in fertility during that interval? In other words, do declines in average parity reflect changes in the composition of the population of married women . . . ~

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117 according to modernizing characteristics, or is it more a case of changes in the parameters that ref lect the impact of these var tables on par ity? The 1 atter are likely to reflect structural changes, and one of the tasks here will be to incorporate in the specif ication variables for which such changes would be indicative of the specific struc- tural forces hypothesized above, that is, increased eco- nomic pressures on household resources. It is important to recognize that questions In censuses and large-scale surveys do not provide a great deal of conceptual precision for the measurement of modernization and its inf luence on fertility. Most of ache measures in this chapter have appeared in the presentation of tabular evidence in earlier chapters; these include income and education, as well as age. A new variable that attempts to measure households' relative economic positions has also been added. Table 38 lists the variables that have been selected for the analysis of data on urban women. Variable labels and a summary of var table def initions are shown. Average parity (CEB), the dependent variable, is listed first. In accounting for variation in this variable, the amount of exposure to the risk of conception needs to be con- trolled. This risk is associated with marital duration Data on age at marriage are Provided only in the 1976 data rile; maternal age is a less satis- factory substitute, particularly at earlier ages when there is greater variability because the marriage is recent. To maintain comparability between 1970 and 1976, regressions were run using maternal age (AGE) as a control for exposure to risk. Women were first separated into three broad age categories, with AGE used as a control variable for each: (1) 20-24, (2) 25-34, and (3) 35-44. To test the sensitivity of results to marital duration (MDUR), the 1976 data were then run using the AGE control variable. The next two variables on the list relate to moderni- zation. It has become fairly standard practice in analy- tical approaches inf luenced by household economic theory to use women' s average educational attainment (MED) and their own and their husband's earnings (HINC) as variables in analyzing differences In average parity (see Schultz, 1976). Women's earnings and educational attainment reflect the opportunity costs of childrearing vis-a-vis other uses of their time, while the earnings of husbands and wives measure their available resources for child- r ear ing and other activities. Theoretically, the effect and maternal age.

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118 TABLE 38 Var table Labels and Def ~ notions, Urban Women: Braz il Var table Def inition CB AGE MED HINC MDUR GAP Average parity: number of live children ever born as reported in 1970 census and 1976 PNAD survey. Mother's age: in years. Mother's education: natural logarithm of the number of years of school completed, def ined as follows: MED-log (years +1), so that log (0 years) "O. Monthly earnings of the head of household: natural logarithm of amount in 1970 cruzeiros. Duration of marriage in number of years for currently marr fed women . Estimated log of head' s monthly earning (PINC) minus log of observed earnings (ZINC). PINC ~ p man, EXP, TAX), where : For ~ years of school completed by head. EXP ~ head ' a age years of school completed - 6 . TAX - natural logarithm of value added tax per capita of state in which woman resides. On the number of children should be negative for cost factors and positive for resource factors; in fact, how- ever, both often turn out to be negative because increas- ing income is usually accompanied by changing attitudes about family size, including a preference for quality rather than quantity of children. Tabular evidence in earlier chapters indicated that differences in average parity in Brazil negatively cor- related with both income and education. However, the question was raised of whether parity changes between 1970 and 1976 mainly reflected changes in the educational and income levels of married women of reproductive age, or whether other variables related to inflation and income distribution also contributed to fertility decline. The available census and survey data files provide only a few threads of evidence on the latter. Increased ownership of televisions, particularly among low-income households

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119 likely to have purchased them on credit, suggests that such factors could have been operative; increased female labor force participation suggests that economic pressures might have contr ibuted to the delay or termination of ch ildbear ing . However, exploratory attempts to incorporate television ownership and female labor force participation in the specif ication of the relationship between female educa- tional attainment, husband's earnings, and average par ity yielded unsatisfactory results. The problem was in iden- tifying the endogenous effects of the employment and earn- ings of women in reproductive ages on their fertility, vis-a-vis the exogenous influence of those women's educa- tion and their husbands ' earnings. The data f iles did not provide other exogenous variables that could be used to estimate fully identified parameters for female employment and earnings. Consequently, the analysis was limited to estimation of reduced-form coefficients; that is, only exogenous variables were included on the r~ght-hand side of the regression equation. In view of this, and to permit continued pursuit of a specification that would capture the effect of the rela- tive economic position of a woman's household (as well as possible changes in that position) on her fertility, an approach based on the concept of relative income was adopted. A households income is relative in that it may be greater or less than the income stream that would be expected on the basis of that household's human capital endowments. A gap between observed and expected income, if it existed, would indicate whether a household was more or less vulnerable to outside economic pressures such as inflation. The approach is consistent with Leibenstein's ( 1974 ) point about the relationship between income and fertility: that while the overall relationship may be negative, it may be positive within specific reference groups, with higher fertility among higher-income house- holds within a particular group. This approach was operationalized by first estimating the expected earnings of husbands using standard earnings equations, and then determining what each husband's earn- ings would be given his particular characteristics. The estimates were based on husband' s earnings rather than household income for s:mplicity's sake (estimates could then be based on the characteristics of one individual without consideration of household size and structure as well as other income sources). Some of the limitations of this approach are offset by the fact that the analysis

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120 was restr ic ted to mare fed women with husbands present who were living in single-family households. Earnings are measured in logarithms of 1970 Cruzeiros per month . The dif ference between repor ted (HINC) and estimated (PINC) earnings provides a measure of the gap described above. Variables in the earnings equation include husband's education in years of schooling com- pleted (HED); husband's experience (current age minus years of schooling minus six [EXP1); and an index of the level of industrial output in the state of residence, which consists of the amount of value-added tax on manu- f actur ing per capita in the state (TAX) . The latter variable was added as a control for regional differences in labor market conditions, which are known to vary widely in Brazil. Earnings equations were estimated for 1970 and 1976, with the following results: 1970: PINC = 3.837 + .149 HEDUC (85.3) (74.S) + .0008 EXP + .249 TAX (1.13 (31.~) 1976: PINC = 4.013 + .158 aEnuc (77.2) (79.0) + .011 EXP ~ .232 TAX (10.9) (25.8) R2 = .38 R2 = .37 Values of the t-statistic are shown In parentheses beneath regression coefficients. A new variable (GAP) was defined as the difference between PINC and HINC. Other variables omitted from the analysis of indi- vidual-level data studied in this chapter were infant and child mortality. Mortality measures for use in analysis of individual records can and have been der ived f rom these data f iles (Metrics, 1981); however, the process of trans- forming ratios of surviving children to children ever born into a normally distr ibuted, jointly dependent var. table would require controlling these ratios for length of expo- sure to risk of mortality using parity progression ratios. It was impossible to specify a statistically meaningful causal relation between fertility and mortality in such circumstances. Unweighted means and standard deviations of the var$- ables used in the regression analysis of differences in average parity are presented in Table 39. The data are broken down according to the three broad age categor ies described above. Exploratory analysis of the relationship between MEI) and CEB suggested a nonlinear specif ication.

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i21 mABLE 39 Meansa (standard deviations) of Variables Used in Analysis of Differences in Average Parity for Urban Women, 1970 and 1976: Brazil Age Year and Variable - 20-24 25-34 35-44 1970 CEB 1.78 3.47 5.00 (1.51) (2.43) (3.51) MED 1.31 1.29 1.17 (0.79) (0. 83) (0. 84) AGE 22.19 29 0 52 39.17 (1. 37) (2. 8S) (2. 84) HINC 5.60 5.76 5.75 (0.92) (1.06) . (1.21) GAP 0.11 -0.01 -0.04 (0. 72) (0. 81) (0. 97) N 2,749 7,532 6,494 1_ CEB 1.45 2.89 4.61 (1. 21) ( 2. 01) t3. 11) MID 1. 67 1. S9 1. 38 (0. 71) (0. 78) (a. 81) AGE: 22.26 29.38 39 e29 (1. 37) (2.76) (2.76) HINC 6.13 6.31 6.27 (1. 02) (1. 07) (1.11) MI)UR 3. 20 8. 23 16.74 (2.26) (4.51) (5.94) GAS 0. 09 -0 .04 -0. 02 (0.86) (0.15) (0.92) N 2, 939 7, 691 6,491 aUnwe ighted sample means.

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122 Consequently, MED was def ined as the logar i thm of a woman's years of schooling completed plus one, so that the logar ithm of zero years of schooling would equal zero. As indicated above, HINC is also measured in logar i thms . S ince GAP is the res idual of the estimated value of ZINC, it has a zero mean for the total study population, but varies slightly from zero ~ n specif ic age categories. Current earnings of husbands of younger women averaged slightly higher than their estimated earnings' while the average GAP for older women fell slightly below zero. I t should also be noted that there are signif icant negative correlations (.7 to .8) between HINC and t:;AP; this indi- cates a tendency for current earnings to be lower than expected earning among husbands with lower earning levels, and for current earnings to exceed expected earns ings by larger amounts among husbands with higher earn- ings. A check of outliers in the earnings equations indicated that these high zero order correlations were a statistical artifact produced by cases at extremes calf the income distr ibution: overestimation of earnings when husbands repot ted zero earnings and underestimate ion when they repot ted very high earnings. These correlations disappeared when extreme cases were omitted; however, it was decided not to exclude such cases from the analysis cuff fertility differentials because the impact of the dif- ferential between ZINC and PINC was of interest over the entire range of the income distr ibution. The data In Table 39 on average marital duration tM=R) in 1976 suggest that analysis of fertility differentials among younger women is likely to be quite sensitive to differences in exposure to the r isk of conception because of the selectivity within that age group toward women who moor ~ -~ "arIV. The ever ace are at mar r iage for women aged ~ ~ _ _, ~ _ —,, , _ _ _ ~ ’ _ _ 20-24 in 1976 was 19.1 years, `:o~arec1 ~o ADOS y="L. I. women aged 25-29. Relative variation in MUIR is also greater among younger women: the coefficient of variation for that group was 71 percent compared to 55 percent for 25-34 and 35 percent for 35-44. Caution is suggested in interpreting results for the youngest age category when MOOR cannot be controlled. Analysis of Urban CEB Differentials in 1970 and 1976 Results of ordinary least squares regression analyst s of differences in CER for women grouped by broad age cate-

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123 gories are presented in Tables 40 (1970) and 41 (1976) Three alternative regression equations were estimated for each data set. In each equation, the AGE var table was included in an attempt to control for length of exposure to r isk of conception within the broader age groups; an additional equation substituting MDUR for AGE in the last alternative is also shown for 1976 . Logar ithms of both MED and HINC were employed af ter initial tests revealed nonlinearity in the relation between these variables and CEB. An education-income interaction term was also int-~o- duced to determine whether the slope of CEB with respect to income shifted with increases in education. Interpretation of regression coefficients for MED and HINC is facilitated by the logarithmic specification, which makes them equally proportional to elasticities (the percentage change in CEB for each one percent change in MED or HINC) e Dividing either coefficient by the mean of CEB gives the elasticity. Comparison between elasticities calculated from the first regression equation for each of the age groups in Tables 40 and 41 and averages for groups of lower- and higher-income countries reported by Schultz (1976) suggests that the responsiveness of BAR to changes in MED and HINC among urban Brazilian women was at an intermediate level, and that it moved in the direction of higher-income countries from 1970 to 1976. Schultz found that elasticities of average par ity with respect to both mother's education and father' s earnings became increas- ingly negative as the level of development increased. This same tendency is observed in the Brazilian data Elasticities for MED are greater (more negative) for younger women, and increase f ram 1970 to 1976. The results for HINC fall more clearly within the range of Schultz's higher-income countries. A spry of the results is as follows: Age Group MAD 1_ BINC 1_ 1970 1_ 20-24 -.30 -.38 -.08 -~07 25-34 -.22 -.31 -,07 -.05 35-44 -.20 -.23 -.07 -.09 Lower -.17 to -.06 +.05 (Schultz) Higher -1.1 to -.19 -.11 to +.28 (Schultz) .

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124 He o m L. a) ED 5: o _I _I N \,. ~ m Ld U] to he O ~ :~ ~ he O ~ Q 00 to a: ~ A HE ~e 1 C) C" ~ _ - O~~ I~ 0- - IY 41 S Po Yl \0 · e O ~ 1 — O ~4 e~e ~ _ ~r _ 1 o o O · . O _ U~ o o '_4 0 · ~ ~ _ ~0 `0 ~ 0, 0. ~ ~ ~ _ ~ ~ ~ _ O _ ~ _ 01 _ ~ ~ ~ ~ \0 ~4 C 4 C~ ~ —~ 1^ ~t ~ O ~ O ~ O t~ · 0 · · · e O ~ 0 ~4e 0 t~ ° ~ Oe ~ O ~e _d _~ —~ ~ C~ ~ _ _ _ ~ _ r _~ · e 0 r~ 1 _I - _ _ 1

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125 .- o o . ,. . ~ AS .- ~ _ ~ : ~ ^ : ~ ~ .- ~ a. ~ ^ o _ ^ =.! a ~ O Z~ ~ ^- ^ ~ . . . . ~ -= ~ O ~ . I . ~ ^ ~ ~ ~ ^ · . · . . · . . ~ ~ e ~ : : . ~ 0= ~ = ~ 2. ~ O ~ ~ :D ~ a = 0 ._ = 0 ~ == ~ O ~ ~ e e ~ ~ ~ =.

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134 by a combination of social, economic, and political forces, many of them longstanding features of rural Brazilian society. One of the most basic of these is the combination of a limited supply of good land and increas- ing population pressure; droughts and infertile soil have plagued areas with a high concentration of rural popula- tion, particularly in the Northeastern states . A second force is the unequal distribution of land, with substan- tial proportions of rural families being forced to eke a subs~sten`:e out of minifundia holdings of fewer than f ive hectares. A third is that there has been increased con- solidation of land holdings ac:companyirtg the co~nmerciali Nation of Brazilian agriculture; this process has received additional stimulus from the energy crisis and Brazil's resultant need to raise foreign exchange through agricul- tural exports and increase production of alcohol as a sub- stitute for petroleum imports. This lack of opportunity in rural areas, combined with hopes of paid employment and urban amenities, has motivated Brazil ' s rural-urban migrations While migration was the primary demographic response to adverse socioeconomic conditions among the masses of Brazil's rural population, other d~rahic processes were affected, including fertility and family formation. Chap- ter 3 suggested several hypotheses about how such changes might be affecting rural fertility in Brazil. All focus in one way or another on the role of children as both immediate productive resources and longer-term ~nves~ents for rural families, and on how changes in rural socioeco~ nomic and institutional conditions could have affected this role e One hypothesis relates to land availability. As the amount of land available to farm families in core densely settled areas is reduced, several forces that could moti- vate not only out-migration, but also lower fertility are set in motion. For families remaining in agriculture that wish to transmit land to their children through inkier zL- ance, large numbers of children will lead to an uneco- nominal subdivision of plots; this can be avoided only by having fewer children, forcing children to start their own families later, Or encouraging the children' s migration. The value of children as immediate productive resources will also be affected to the extent that smaller plots reduce the need for child labor. The influence of these forces on reproductive behavior is mediated by institutional f actors and by the availabil- ity of new land in other areas. Research on land avail-

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135 ability and fertility in rural Brazil using data from the 1970 censuses of population and agriculture found that fertility was lower in more densely settled regions of Southeastern Brazil and higher in areas of new rural set- tlement in the Central-Western region (Merrick, 1974). An extension of that research to Northeastern Brazil and to the frontier settlements in the Amazon region did not reveal similar patterns (Merrick, 1981). Several reasons for this were suggested: get underway until after 1970, and the very- unequal dis- tribution of access to land in the Northeast was not as conducive to the pattern observed in the South, here a higher proportion of family farms were owner~operatede Research with 1970 data also revealed the very severe limitations of population census data for dealing with links between rural demographic changes and socioeconomic and institutional factors affecting those changes. These limitations were overcome to some extent by combining pop- ulation census data with information from the agricultural census. Analysis of changes during the 1970s will have to await the availability of detailed information from the 1980 censuses of agriculture and population. Onfortu- nately, the PNAD surveys taken during the 1970s do not provide the geographic detail required for linking them to results of Me 197S agricultural census; moreover, the PNAD sample does not include rural areas of the Central- West and Amazon regions, so that the potential positive effects on fertility of frontier settlement in those regions during the 1970s cannot be examined. Some features of the relationship between fertility decline in rural Brazil during the 1970s and socioeconomic change in the areas included in the PNAD surveys can be studied. One of these relates to an institutional factor mediating the response to increasing economic pressures, such as scarcity of land and consolidation of land in larger holdings, on Me demographic responses of farm families. This factor is rural proletarianiiation, or the shift from an owner~operator and farm family labor mode of production to wage labor. As noted earlier, European experience, as well as evidence from Southern Brazil, indicates that lower fertility is more likely to result from a scarcity-of land when farm families own their land and reduced fertility allows them to maintain control of the land. Rural proletarianization weakens this motiva- tion. As noted in Chapter 3, Paiva (1982) disagrees with this interpretation for Brazil. Be argues that prole- tarianization reduces the value of children as farm Amazon settlement really did not

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136 laborers and provides incentives for reduced fertility, including increased market work for both women and chil- dren. The potential value of market work would be increased by education, and by a shif t toward quality rather than quantity of children. The data with which to evaluate these two interpreta- tions of Brazilian exper fence are scant. Tabular evidence presented in Chapter 3 indicated that average parity was indeed lower in reg ions with higher levels of proletar ian- ization (measured according to the proportion of rural household heads reported as employees ); irt the same tables, however O average parity was higher rather than lower for proletarian households within those regions. While one must be caret ul to avoid the f allacy of compoo sition, one must also be careful about biases ar ising f ram the location of families when their characteristics have For rural areas, those data detect only that proportion of the proletar- been measured in census and survey data. ionized population remaining at the time News were conducted; those who moved (either to urban areas or to other rural areas) and who may well have had lower fer- tility would not be included. Another aspect of change in rural fertility relates to the socioeconomic differentials observed in Chapter 2. Bile these differentials were not as great as those observed in urban areas, the data presented in Chapters 2 and 3 indicated that rural women with some education had lower fertility than those with no education, and that the proportion of rural women with some education increased from 1970 to 1976. Also, rural women with no education as a percent of all women aged 15-49 declined from about 21 percent to about 13 percent, a result of some comb~na- tion of increases in ectuca~zona~ acca~rmer~c arcane Lucas women, out-migration, and possible underrepresentation of less-educated rural women in the PNAD survey. Such evi- dence suggests that the role of education should not be neglected in examining rural fertility differences. Analysis of Rural CEO Dif ferentials in 1970 and 1976 As indicated above, neither the 1970 census nor the 1976 PNAD survey provides many meaningful measures of concepts relevant to the analysis of changes in rural fertility in Brazil. The multivariate analysis that follows is pre- sented primarily to illustrate how the relationships between differences in average parity and socioeconomic

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137 vat tables descr ibed for urban women compare to the case of rural women. No pretense is made of even approximating a comprehensive explanation of changes in rural reproduc- tive patterns based on these data . Table 46 lists the variables included in the analysis. Average parity (FOR) iS the dependent variable, and educa- tion of women (MED) Is included in logarithmic form as it was for urban women. Census and survey measures of income and earnings had so little conceptual content for the r ural population that they were quickly abandoned O lIuso band' s education (=n) has been substituted as a proxy measure of earnings potential, but no attempt was made to calculate the gap between actual and potential earnings. Two additional dummy variables were employed: one for residents of Northeastern states (NE:) F included to pick up the effects of regional differences in economic and social structure not reflected in education, and one to indicate if the household was proletarian {PROL), based on whether or not He husband's status was reported as employee or paid farm laborer. Unweighted means and standard deviations of these variables are shown in Table 47. Average CEB declined by 12 percent for married women aged 20-24, 6 percent for TABLE 46 Variable Labels and Definitions, Rural Women: Brazil van table Def inition - C~R AGE MED HEI) NE PROL Average par itys namer of live children ever born as reported in 1970 census and 1976 CHAD survey. Moocher 's age: in yews. Mother's educations natural logarithm of the nudger of yews of school completed, defined a. follows Clog (years +~), so that log (O years)-O. Father's educations nat=^ logarithm of the number of years of school completed, defined ~ follows HED-log (years Al), so that log (0 ye~)-O. Northe~ts day Variable equal to one for residents of northeastern states. Proletarians day variable equal to on. when es~plo~nt stat" of father is rural wage labor.

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138 TABLE 47 Meansa (standard deviations) of Variables Used in Analysis of Differences in Average Parity for Rural Women, 1910 and 1976: Brazil Age Group Year and Variable 20-24 25-34 35-44 1970 1976 CEB 2.21 4.42 6.79 (1070) (2071) (3.82) MED 0. ~2 0.53 0 0 41 (DO 66) (0. 67) (0. 61) HED 0.53 0.56 0.49 (0. 66) (0. 67) (0. 64) AGE 22.07 29.17 39.01 (1.42) (2.87) (2.79) NE 0. 45 0.43 0. 43 {0. 49) t O. 50) (0. 50) P - L 0.31 0.30 0.26 (0046) (0.46) (0. 44) N 2,456 4,880 4,108 CEB 1.95 4.14 6.73 (~.50) (2.57) (3.62) ME 0O90 0.78 0.61 (0. 75) (0 O 74) (0 O 70 3 lIED 0.84 0 0 76 0. 65 (0.74) (0.73) (0.71) AGE 22 a 17 29 ~ 26 39 ~ 21 (lo42) (2~85) (2~89) NE 0~32 0~33 Oc31 (Oe47) (0~47) (0~46) PROL 0.48 0.43 0. 38 (0. 50) (0. 49) (0. 48) N 2~344 5~247 4~615 al;lnweighted sample means.

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139 those aged 25-34, and less than ~ percent for those aged 3 5-44. Relative var iation in average Rapt was somewhat lower for rural than for urban women. For women in the 2 5-34 age group Of the coef f ic lent of var iation ( ratio of the standard deviation to the mean) was 0.61 in 1970 com- pared to 0.7 for urban women. In 1976, relative variation increased, and was close to the level observed for urban women. There was a greater proportional increase in aver- age education for women than for men, with the greatest increase occurring among ages 20-24. The Northeast was represented less in 1976 because of a smaller sampling fraction for that region in POND (as well as possible underrepresentation in the Samoyed. ~__, The proportion of women in proletarian households increased for all three age groups, again with the greatest increase among younger women. Multivariate regression results for 1970 are presented in Table 48, and those for 1976 in Table 49. Separate regressions were run for each of the three broad age categories, with a control for age within each category as cell. Three regressions were selected for each group: the first includes, in addition to AGE, the education variables MED and ~ the second adds the dub variable for the Northeastern states (NE); and the third includes the dummy variable for proletarian households (PROLl. Since both MED and "D enter in log form, their regression coefficients are again proportional to elasticities (which are derived by dividing the coefficients by the sample mean value of I). A sugary of the elasticities of If with respect to average MED and BED is as follows: Year 20-24 25-34 3S-44 . MED ID MED BED ME ID 1910 -.16 -.06 -.10 -.02 -~04 -.01 1976 -. 16 - .10 ~ .15 -. 06 -.07 -. 08 Compared to the results for urban women, the responsive- ness of CEB to increases in MED is one-third to one-half as great for rural women, and the increase in responsive- ness from 1970 to 1976 is smaller. Compared to results for the range of countries reported by Schultz (1976), results for older rural Brazilian women are close to the bottom of the range of elasticities for lower-income coun- tries (-.17 to -.04) and for younger women near the top. Although addition of the dummy variable for residence in Northeastern states (the second set of equations) does not add significantly to the amount of variance explained,

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140 ~, _ - m C) - _ ~4 d . - C) o ~4 Q L. C. ~Q ·~4 U; :- ·e O fo ~: ~ ~ ' O ~ · ~o ~o O ~ 3 E~: ·d m E~ x: a 3' z 8 o~ ~ o a: V ~ ~ ~ ~ ~ ~ U. o o o o o o o o, o o o o o o ~ ~ ~ o ~ o ~o o ~ o o o ~ o ~ o ~ o ~ o ~ ~ ~La _ ,_~ _ <7~~ _ ~~ _ ~ _ ~ _ ~ _ ~ _ a, ~o U1 ~ iD ~ ~ ~. ~ _ _ _ _ _ ~' C'4 ~ _. ~ ~ ~ _ _ 01 ~ ~ ~ O O \0 0 \0 ~ `0 ~ ~ ~ ~ ~ ~ O ~ O ~ O ~ ° a O O C-4 0 O4 0 C~ O ~ O \0 0 `0 0 ~ O ~ O ~ _~ _ _ _ _ O _ ~ _ ~ ~ ~ ~ 0 0 ~ 0 ~ 0 r~ · a · 0 a a O ~ O ~ O O _ _ _ 0 _ a~ ~ ~ ~ ~ _ o. _ ~ _ C~4 ~ C~ \0 ~ U' ~ ~ ~ ~ ~ `0 - 4 `0 ~ 1— ~ r~ ~ r~ ~o ~ ~o ~ · a 0 0 · 0 ° · · a a a O _. O _' O ~ O ~ O U' O 1^ - - - - - - a, _ ~ ~ r~ ~ ~ _ ~ _ ~ ~ ~4 — ~ — ~ — 0 ~ 0 ~ O ~ ~ u1 ~ r~ ~ ~ ~ ~ ~o r~ ~ ~ ~ co ~ ~ ~ \0 ° a ~ ~ a ~ ~ a 0 ~ 0 ~ 0 ~ 0 ~ 0 ~ 0 ~ 0 ~ O ~ O r~ _t _l _1 C~ ~ ~ _ _ _ _ _ _ _ _ _ r" _ ~o _ ~ _ c~ _ r~ _ ~ _ ~ _ \0 _ ~ _ 0 \0 ~ ~ ~ ~ ~D O (D ~ ~ co ~ ~ (D u~ C— u~ U1 ~ ~ ~ O ~ ~ ~ r~ 0 ~ ~4 0 0 ~ O r~ a ~ a · a · ~ a e a 0 c~4 0 r~4 0 r~ 0 ~ 0 ~ a ~ 0 ~ 0 0 0 0 I _ t — I _ I _ I _ I _ I _ I _ I _ o _ ~ ~ O O _ ~ _ ~ _ O _ ~ _ ~ _ _ . _ ~ ~ ~ S N ~ ~ ~ ~ ~ q. ~ ~ - 1 0` O1 ~ C~ ~ ~ ~ · · · e ~ ~ 0 0 ° a ~ · O 0 C O ~ O ~ O ~t O ~ O `0 ~ 0 O4 0 ~ O N 1 — 1 — 1 — 1 — 1 — 1 — 1 — 1 — 1 — a. `: 4S ~ ~ ~ _ In _ r~ ~ ~ _ u' _ ~ _ ~ _ u~ _ —4 '0 ~ ~ _~ _~ ~ ~ ~ r~ d t~ t~ ~ ~ ~ O {m ~— t~ ~n ~@ ~ (~ ~o \n c~ ~ ~ ~ (D O ~ O · a ~ a 0 ~ a ~ ~ ~ ~ ~ 0 ~ ~ ~ ~ ~ ) ~ ~ ~ ~ ~ _1 ~ C~ ~ C~ O O O O O O 1 — 1 — 1 — 1 _1 1 ~ 1 _. — — — _ _ _ _ _ _ ~ _ ~ ~ _ _ _ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ C~ ~ 1 _ _ — 1 _ _ — 1 _ _ _ O - ·~~ U~ O1 as - o z

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141 CD - ~: s~ o s~ ~ — - c~ cn a: x: - o. O ~ ~ Z z s" . N ~ m - £ :~ o a~ at 0 _ m 6 ~ ~ ~: o o o · ~ ~ _ In _ ~ _ ~ U' ~ O4 r~ ~ r. o ~ o ~ o ~ o ~ _ _ y ~, ~o z o o. :, o C' o o O4 o · . r. — - 0 r" r~ ~4 · ~ o U~ - o o o · — o _ - o O4 r~ · ~ O U1 - o o o · ~ ~ _ U' o O4 · ~ o ~ o o mo · . ~ _ o cr. o ~ · ~ o ~ - o ~ · ~ o ~ - _ ~ _ r~ _ ~ _ ~o _ ~ ~ ~ _ ~ o~ 0 ~ ~o ~r~ ~o t~~. ~ _~ ~ ~ ~ ~ ~ 0 r~ 0 ~ ~ ~ o, ~ ~ r~ ~ c.4 ~ r~ ~ ~ c*4 ~ r~ ~ ~ e ~ · e · ~ · ~ ~ · · e ~ · · O ~ O ~ O ~ O \0 0 ~ O ~ O ~ O ~ O 1 — 1 — 1 — 1 — 1 — 1 — 1 — 1 — 1 — _ ~ O _ O _ ~ _ ~ _ ~ _ ~ _ C~ ~ — ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ —~ O ~ O `° ~ 10 10 eC ·q ~ ~ t_ ~ r— ~0 ~ 40 /X~ ~0 ~ 1^ ~ ~ ~ O · ~ e ~ · ~ · ~ 0 ~ · ~ · O ~ O \0 0 \0 0 ~ O _. O _. O 10 0 It' O It, 11, 1 — 1 — 1 — 1 _. ~ _' 1 _1 1 — 1 — 1 — _ _ _ ~ _ ~ _ O O ~ ~ _' 0 ~n · 0 · ~ ~0 1 — ~ _ ~ _ C~ ~ 1 _ o r~ I_ — 1 r~ 0 ~ 0 ~ r~ - 4 o ~ ~ ~ ~ ~ · · · · · ~ ~ ~ o o o o c) ~4 r~ o ~q :n

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142 the regression coefficient is signif icant for the two older age groups. This indicates an interaction between education and residence rather than an additive effect. Tests for the interaction suggested that MED slopes were lower in the Nor the es t, though so few rural women in the t region reported any education that it was difficult to judge the signif icance of the results. The third set of equations attempted to assess the impact of proleSar ionization on average CEB. The results were consistent with the tabular results in Chapter 3, which suggested that CEB was slightly higher in praletar- ian rural households c When other var tables were con- trolled, however, this difference was signif icant only f or women in the 25-34 age group in 1976. These results conf irm the point made earlier that an adequate test of the proletarian hypothesis will require a more precise measurement of the process of proletar ionization that captures present and previous res idence and occupational status, as well as a r icher depiction of the institutional forces underlying that process. Changes in Rural CEB from 1970 to 1976 The change in average CEO from 1970 to 1976 that can be accounted for in the regression analysis results from increased educational attainment. In this connection, it should be recognized that mos t of the observed change is not explained by changes in the var. tables included in the regressions. It Is hoped that the case study data reported In Part lI of this report w~11 provide richer insight into the nature of changes in rural fertility than do aggregate census and sample survey data. CONCLUSIONS Most of the variance in average par ity that can be explained by application of multi~rar late regression anal- ys is to data on individual mar r fed women f rom the Braz il- ian census and PNAD survey relates to modernization variables--education and average earnings. Most of the change that can be accounted for betweer~ 1970 and 1976 relates to increases in these two var tables. The attempt to incorporate a var table measur ing the relative economic position of urban households indicated that there was a positive association between fer tility and relative eco-

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143 nomic status; that is, CEB was higher on average for women whose husbands' current earnings exceeded the level of earnings that would be expected given their education and other characteristics. However, decomposition of changes in CEB from 1970 to 1976 did not show that a change in GAP contributed to fertility decline. These regression results do not suggest that increased modernization was the only reason for the change in Bra- zilian fertility. Changes in regression coeff icients and in constant terms in the regression equations suggested that a variety of unmeasured factors could account for the unexplained variance. Measures that were available in the census and survey data provided little insight into the nature of such changes, whether related to increased access to contraception through public or private chan- nels, or to institutional changes associated with shifts in the Brazilian raodel of socioeconomic development. It should also be recognized that average parity is a poor measure of fertility for purposes of accounting for change. It is a cumulative variable, and comparisons of averages for different groups at different dates measure the result of a demographic process rather than the pro- cess itself. As noted above, it would have been better to use current fertility as measured by births reported for the year prior to the interview' however, as reported in Chapter 2, the performance of that measure inspired more confidence in its robustness for work with subgroups of the population. Attempts to derive other measures (such as the length of the first open birth interval) from these data files procured equally unrewarding. Data limitations curtailed even further the analyst s of differences and the decomposition of changes in the average parity of rural women. The main finding for these women was that increased educational attainment contri- buted most to the explanation of variance, though only a limited portion of the total variance was explained by the regressions. Some doubts were raised about the hypothesis that proletarianization contributed to fertility decline; however, caution was suggested about the validity of using data on rural women classed as proletarian at the time of the interview to test this hypothesis, rather than using the experience of the proletarianization process. It was also impossible to link what the census and sur- vey data reported about the demographic characteristics of individual rural residents and their families to eco- nomic characteristics of their farms and institutional features of their localities. For this reason, the study

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144 could not explore hypotheses relating fertility decline to changes in land availability, reduced need for child labor, and increased nonfarm economic activity for rural women and children. The census and survey data f iles did include questions on school attendance that mer feed fur- ther study. Information on child labor was included In agricultural censuses, but not In the demographic censuses and surreys. If Brazil is ever to conduct a fertility survey patterned after the World Fertility Survey, it would focus ideally on these elements of rural socioeco- nomic structure, as well as those aspects of change in urban areas that are not covered by currently avail able census and survey data.